'Lagrangian Saddle Point and Wolfe Dual' Video Lecture

Lagrangian Saddle Point and Wolfe Dual

  • Course: Numerical Optimization
  • Discipline: Computer Science and Engineering
  • Faculty: Dr. Shirish K. Shevade
  • Institute: IISc Bangalore

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    Course Video Lectures Introduction Mathematical Background Mathematical Background (contd) One Dimensional Optimization - Optimality Con.. One Dimensional Optimization (contd) Convex Sets Convex Sets (contd) Convex Functions Convex Functions (contd) Multi Dimensional Optimization - Optimality C.. Line Search Techniques Global Convergence Theorem Steepest Descent Method Classical Newton Method Trust Region and Quasi-Newton Methods Quasi-Newton Methods - Rank One Correction, D.. i) Quasi-Newton Methods - Broyden Family ii) .. Conjugate Directions Conjugate Gradient Method Constrained Optimization - Local and Global S.. Feasible and Descent Directions First Order KKT Conditions Constraint Qualifications Convex Programming Problem Second Order KKT Conditions Second Order KKT Conditions (contd) Weak and Strong Duality Geometric Interpretation Lagrangian Saddle Point and Wolfe Dual Linear Programming Problem Geometric Solution Basic Feasible Solution Optimality Conditions and Simplex Tableau Simplex Algorithm and Two-Phase Method Duality in Linear Programming Interior Point Methods - Affine Scaling Metho.. Karmarkar\'s Method Lagrange Methods, Active Set Method Active Set Method (contd) Barrier and Penalty Methods, Augmented Lagran.. Summary
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